Involvement Load Hypothesis (ILH) and Technique Feature Analysis (TFA) are two frameworks which operationalize depth of processing of a vocabulary learning task. However, there is dearth of research comparing the predictive power of the ILH and the TFA across second language (L2) vocabulary learning tasks. The present study, therefore, aimed to examine this issue across four vocabulary learning...

One of the most obviously striking features of human language, especially in comparison with all other communication systems in nature, is syntax. More precisely, language is unique in providing an open-ended system for relating signals and meanings, one which has its own internal structure. The particular structure of the mapping between meanings and signals varies from language to language, a...

The Lexical Knowledge Representation Research Group at the Department of Lexicology is one youngest research groups Hungarian Centre for Linguistics, founded in February 2020. group currently working on a new version monolingual explanatory dictionary partly based Explanatory Dictionary Language. aim to compile an up-to-date online contemporary (2001–2020) by corpus-driven methods. present arti...

How deeply a word is processed has long been considered as a crucial factor in the realm of vocabulary acquisition. In literature, two frameworks have been proposed to operationalize the depth of processing, namely the Involvement Load Hypothesis (ILH) and the Technique Feature Analysis (TFA). However, they differ in the way they have operationalized it specially in terms of their attentional c...

This paper presents a computational model of language learning, transmission, and evolution. We contrast two explanations for the observed t of language universals with language function that are prominent in the linguistics literature, and which appear to rely on very diierent explanatory mechanisms | innate constraints on the one hand, and parsing innuenced language change on the other. We sh...